Artificial intelligence is the future. If "Westworld" or "Black Mirror" are to be believed, there will soon come a day when the computers rule us all. The USPTO has denied a pair of patents filed on behalf of DABUS, an artificial intelligence system, and published a ruling that says US patents can only be granted to "natural persons." The two patents were for a food container and a flashlight, and were filed by Stephen Thaler, an AI researcher and DABUS' creator. According to the filing from the USPTO, Thaler calls DABUS a "creativity machine" and wanted the AI to get full credit for the inventions. The filing says Thaler argued that "allowing a machine to be listed as an inventor would incentivize innovation using AI systems."

Arcade expert and hot sauce mogul Billy Mitchell made a name for himself by earning record-breaking scores in games like Pac-Man and BurgerTime. Two years ago, de facto scorekeeper Twin Galaxies stripped Mitchell of his Donkey Kong records after concluding that his most recent score was not achieved on authentic arcade hardware. Mitchell refuted this, and in September of 2019, the gamer and his lawyer announced they'd be taking Twin Galaxies to court, after claiming that the company had defamed his name. According to Ars Technica, Mitchell had, in fact, already filed suit in April of 2019, as to avoid California's statute of limitations running its course. The case was served to Twin Galaxies this February, and a hearing will be held in July.

The sudden suspension of a controversial multi-million dollar surveillance system used by several government agencies in Utah has opened up a debate about the lack of oversight for artificial intelligence systems in law enforcement. Last week, the Utah Attorney General's office suspended a $20.7 million contract with Banjo -- a technology firm using government surveillance data to develop crime detection software -- following revelations of the founder's past membership of a white supremacist group. Damien Patton, who serves as CEO of the SoftBank-backed company, was reportedly an active member of the Ku Klux Klan as a teenager, and participated in a 1990 drive-by shooting of a synagogue in suburban Nashville, according to the tech blog OneZero. In a statement, a spokesperson for Utah Attorney General Sean Reyes said the office would be moving forward an already planned third-party audit of the software to "address issues like data privacy and possible bias." Reyes recommended that other state agencies do the same.

The right to be forgotten states that a data owner has the right to erase her data from an entity storing it. In the context of machine learning (ML), the right to be forgotten requires an ML model owner to remove the data owner's data from the training set used to build the ML model, a process known as machine unlearning. While originally designed to protect the privacy of the data owner, we argue that machine unlearning may leave some imprint of the data in the ML model and thus create unintended privacy risks. In this paper, we perform the first study on investigating the unintended information leakage caused by machine unlearning. We propose a novel membership inference attack which leverages the different outputs of an ML model's two versions to infer whether the deleted sample is part of the training set. Our experiments over five different datasets demonstrate that the proposed membership inference attack achieves strong performance. More importantly, we show that our attack in multiple cases outperforms the classical membership inference attack on the original ML model, which indicates that machine unlearning can have counterproductive effects on privacy. We notice that the privacy degradation is especially significant for well-generalized ML models where classical membership inference does not perform well. We further investigate two mechanisms to mitigate the newly discovered privacy risks and show that the only effective mechanism is to release the predicted label only. We believe that our results can help improve privacy in practical implementation of machine unlearning.

Artificial intelligence is the future. If "Westworld" or "Black Mirror" are to be believed, there will soon come a day when the computers rule us all. But for now, an AI's power ends at the US Patent Office. The USPTO has denied a pair of patents filed on behalf of DABUS, an artificial intelligence system, and published a ruling that says US patents can only be granted to "natural persons." The two patents were for a food container and a flashlight, and were filed by Stephen Thaler, an AI researcher and DABUS' creator. According to the filing from the USPTO, Thaler calls DABUS a "creativity machine" and wanted the AI to get full credit for the inventions.

Last summer it was reported that patents had been filed in the USA and Europe listing an artificial intelligence system as the inventor. The patents in question were for a food container and a warning light and were filed by Stephen Thaler on behalf of DABUS (an AI system). Those applications have been considered, and on 22 April the US patent and trademark office (USPTO) reached the same verdict as the UK and European offices, denying the patents. In his application Thaler asserted that the inventions were generated by DABUS (which he dubs a "creativity machine"), and that the system was not created to solve any particular problem. He claims it was, therefore, the machine, not a person, that recognised the novelty of the invention. The USPTO ruled that applications require the inventor to be a "natural person", and denied the patents on that basis.

Human trafficking is a huge problem which has at times proved so difficult to solve. Largely operated by criminal organisations, there is often a lot of money involved in trafficking. Whilst money remains a massive incentive for criminal gangs, often trafficking is motivated by pure greed and lust – notoriously the'grooming gang' of Rochdale. Artificial Intelligence (AI) has recently been crucial in bringing traffickers to justice, so how do we use AI to put a stop to this? AI is already having a huge impact on human trafficking investigations in some parts of the worlds. Traffic Jam is a project started by American tech company Marinus Analytics.

We are seeing AI technologies increasingly deployed across many parts of society. Around the globe, governments are rushing to mobilize vast amounts of capital to invest into AI innovation. The COVID-19 pandemic prompts us to rethink what is considered high- or low-skill work. Whose skills, whose labor and whose hours, exactly, are of value to society? What and who do we value and deem essential, and how do we compensate these workers (e.g., care work or teaching)?

The ethics of AI and robotics is often focused on "concerns" of various sorts, which is a typical response to new technologies. Many such concerns turn out to be rather quaint (trains are too fast for souls); some are predictably wrong when they suggest that the technology will fundamentally change humans (telephones will destroy personal communication, writing will destroy memory, video cassettes will make going out redundant); some are broadly correct but moderately relevant (digital technology will destroy industries that make photographic film, cassette tapes, or vinyl records); but some are broadly correct and deeply relevant (cars will kill children and fundamentally change the landscape). The task of an article such as this is to analyse the issues and to deflate the non-issues. Some technologies, like nuclear power, cars, or plastics, have caused ethical and political discussion and significant policy efforts to control the trajectory these technologies, usually only once some ...

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